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Yaniv Azar
Researcher at New York University
Publications - 11
Citations - 8616
Yaniv Azar is an academic researcher from New York University. The author has contributed to research in topics: Encoder & Pixel. The author has an hindex of 6, co-authored 11 publications receiving 6690 citations.
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Proceedings ArticleDOI
28 GHz Angle of Arrival and Angle of Departure Analysis for Outdoor Cellular Communications Using Steerable Beam Antennas in New York City
Mathew K. Samimi,Kevin H. Wang,Yaniv Azar,George N. Wong,Rimma Mayzus,Hang Zhao,Jocelyn K. Schulz,Shu Sun,Felix Gutierrez,Theodore S. Rappaport +9 more
TL;DR: This work shows that New York City is a multipath-rich environment when using highly directional steerable horn antennas, and that an average of 2.5 signal lobes exists at any receiver location, and proposes here a new lobe modeling technique that can be used to create a statistical channel model for lobe path loss and shadow fading.
Proceedings ArticleDOI
Detection of falsification using infrared imaging: Time and frequency domain analysis
Yaniv Azar,Matthew Campisi +1 more
TL;DR: By measuring temperature changes in the nose area, one could determine whether someone is lying or not better than current polygraph can and that it is possible to detect lies using an infrared camera since it has higher accuracy, is non invasive, and cost effective.
Proceedings ArticleDOI
It’s All About The Scale - Efficient Text Detection Using Adaptive Scaling
TL;DR: In this paper, a segmentation-based network with an additional "scale predictor", an output channel that predicts the scale of each text segment, is proposed to estimate this prior, which is applied on a scaled down image to efficiently approximate the desired prior, without processing all the pixels of the original image.
Posted Content
It's All About The Scale -- Efficient Text Detection Using Adaptive Scaling
TL;DR: A segmentation-based network with an additional "scale predictor", an output channel that predicts the scale of each text segment that is applied on a scaled down image to efficiently approximate the desired prior, without processing all the pixels of the original image.
Proceedings ArticleDOI
Polarization diversity measurements at 5.8 GHz for penetration loss and reflectivity of common building materials in an indoor environment
TL;DR: The results show that combinations of vertical-vertical and slant 45° - vertical polarization pair have relative low penetration losses and high reflectivity, meaning that the signal would be contained within a room or within the hallway in such environment with an in-building base station.